Does NGD converge to minima that are 'more complex' i.e. have a higher RLCT?

model_type: ffnn
experiment_type: standard
optimizer: both
hessian: True
hidden_nodes: [64, 128, 256, 64, 128, 256]
hidden_layers: [1, 1, 1, 2, 2, 2]
hidden_conv_layers: [0]
cut_off_epochs: 20
num_epochs: 20
sgd_lr: 0.01
ngd_lr: 0.01
alpha: 0.01
eta: 0.9
epsilon: 1e-10
delta: 0.0005
momentum: 0.9
nesterov: True
seed: 1
batch_size: 2048
num_workers: 32
dataset: mnist
num_hessian_batches: 1
sampler: sgld
num_chains: 2
num_draws: 1000
localization: 100.0
sampler_lr: 0.0001